VANTED - Visualization and Analysis of Networks containing Experimental Data


VANTED is an open-source Java-based extendable network visualisation and analysis tool with focus on applications in the life sciences. It allows users to create and edit networks, and to map experimental data onto those networks. Experimental datasets can be visualised on network elements to show time series data, data of different treatments, environmental conditions and so on in the context of the underlying biological processes. Analysis algorithms allow an easy and fast evaluation of data-enriched networks.

The functionality of VANTED can be easily extended by installing one or more of the provided Addons using the built-in Addon Manager. For an overview see [here] New Addons can be developed from scratch, using built-in APIs for manipulation of networks and data. A simple step-by-step guide for developing custom Addons can be found [here].

The development of VANTED is an ongoing process and we try to fix bugs and implement new features as soon as possible. Updates will be delivered on a regular basis.

Develop on and for VANTED

VANTED is open source and can be used and changed at your will.
The source code is hosted on BitBucket [link] as a GIT repository. To find out more about how to get the source code and develop Add-ons for VANTED, go to the [WIKI] .
Happy Coding!

References

Please cite one of the following papers if you use VANTED in your research:

Hendrik Rohn, Astrid Junker, Anja Hartmann, Eva Grafahrend-Belau, Hendrik Treutler, Matthias Klapperstück, Tobias Czauderna, Christian Klukas and Falk Schreiber (2012): VANTED v2: a framework for systems biology applications BMC Systems Biology 2012, 6:139

Björn H. Junker, Christian Klukas and Falk Schreiber (2006): VANTED: a system for advanced data analysis and visualization in the context of biologicalnetworks BMC Bioinformatics 2006, 7:109

If you have used one of the Add-ons found on the Add-on-Site, please use their citation.

Contact

Development supervision: 

   * Prof. Dr. Falk Schreiber,
      University of Konstanz
      Life Science Informatics 

Main development by: 

   * Dimitar Garkov,
   * Matthias Klapperstück
   * Dr. Tobias Czauderna,
   * Dr. Hendrik Rohn,
   * Dr. Christian Klukas